COMP SCI 3013 - Event Driven Computing
North Terrace Campus - Semester 2 - 2017
General Course Information
Course Code COMP SCI 3013 Course Event Driven Computing Coordinating Unit School of Computer Science Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 2.5 hours per week Available for Study Abroad and Exchange Y Prerequisites One of COMP SCI 1007, COMP SCI 1009, COMP SCI 1103, COMP SCI 1203, COMP SCI 2103 or COMP SCI 2202 Assumed Knowledge COMP SCI 2006 Course Description Event driven paradigm: Finite State Automata, their behaviour and implementation. Correspondence with regular expressions. Examples of embedded systems. Introduction to interconnected state machines, Petri Nets, and concurrency. Concepts of state-space and relationship to testing. Push-down automata and applications to parsing. Building Graphical User Interfaces: model view controller paradigm. Building GUIs using modern APIs. Ease of use and human-computer interaction issues.
Course Coordinator: Dr Sergey Polyakovskiy
The full timetable of all activities for this course can be accessed from Course Planner.You can find the schedule of lecture topics on the course webpage:
Course Learning OutcomesOn successful completion of this course students will be able to:
1 Describe the different ways a finite-state machine can be represented 2 Explain how a finite state machine recognises an input string 3 Explain how a non-deterministic finite state machine works 4 Explain the behaviour of regular expressions 5 Translate a regular expression into a corresponding finite-state machine 6 Build GUI-based software systems 7 Explain a few basic design-patterns, and know when to apply them
The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
The course is designed to develop the following Elements of Competency: 1.2 1.3 1.6 2.1 2.2 2.3 2.4 3.3 3.4 3.5
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
5 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
4,5 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
1,2,3,4 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
5,6,7 Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, diffuse conflict and engage positively in purposeful debate
Required ResourcesThere is no required text-book.
Comprehensive lecture notes are available for most parts of the course.
Recommended ResourcesYou can perform all the exercise work required for the course in the University computer Labs.
The programming language used is Java, which is similar to C++ (but with most of the disgustingness removed...)
However, if you want to be able to work at home, you could consider installing Java on your own system.
For more information, go to the Java website --- simply Google "Java".
Online LearningYou can find the general information about this course at www.cs.adelaide.edu.au/~third/edc
Specific information about this year's offering can be found under the heading "current offerings" near the top of the page. Links to lecture-recordings, examples, exercises, and tutorials will be posted on this page.
Learning & Teaching Activities
Learning & Teaching ModesThe course will be taught with lecture/demonstration sessions.
There will also be tutorial classes, and practical exercises.
You are expected to attend the lectures and take part in the activities, and attempt tutorial questions before the scheduled tutorial session.
All lectures will be recorded, but things can go wrong --- equipment failure, lecturer failure, etc.
It is unwise to rely on the recordings as your only source of the lectures.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.You are expected to attend all scheduled lecture classes (2hrs per week).
In addition to the schedule contact hours, you are expected to spend an additional 2-4 hours per week after each lecture to consolidate your understanding of it.
You will need to allocate up to 5 hours per week to work on the assignments and tutorials.
Learning Activities SummaryThere is an approximate schedule of the topics that will be covered on the course website.
The exact timing will depend on the times of public holidays and other eventualities.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment SummaryThe assessment will comprise two parts:
Three programming exercises (10%+10%+10%); and
A final exam (70%).
Assessment DetailAll practical assignments require you to write programs, which will be marked by an automatic testing script.
You are strongly encouraged to begin the exercises early, to allow time for seeking help when needed.
You will find that the marking script is aggessively hostile --- it will seek to break your program.
To encourage you to test your own program, access to the tester may be limited to a fixed number of test runs.
The first test run will occur on the due date for the execise, and the subsequent two runs will be at about 4-day intervals afterwards.
The test script does not tell you exactly what is being tested, and may provide little or no information that is useful in finding errors.
If you submit your exercise at the last minute, and hope to use the automated tester to help you debug your program, you will be seriously disappointed.
You should build your program in small stages, and test it thoroughly.
The testing regime is like this because, you will most likely soon graduate, after which there will be no more automatic testers available --- you will need to learn how to test, and write you own testers.
SubmissionAll practical assignments must be submitted using the School of Computer Science online Submission System.
Details are included in each assignment description on the course website.
At the time of submission, some elementary tests will be run to ensure that your program is fundamentally OK.
If you fail any of the handin tests, you will likely fail almost all of the real tests...
If you hand in your work late, you will miss the test-runs, and deprive yourself of vital evidence that might help you debug your program.
Start early, test often!
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.You can find the latest SELT survey results on the course website, here:
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